Achieved more than 50% reduction of instance costs for a savings of over $1.1 million over 14 months.

Ran 50% more tasks on one of their largest clusters.

Achieved a 30% cloud cost reduction within a week and an average monthly savings of $7800.

Achieved a 95% infrastructure utilization and a 23% cost savings on Amazon EMR.

Achieved almost $5 million in annualized savings and exceeded 200% ROI.

Achieved annualized savings of over $600K.

Achieved a 24% increase in task performance and saved $30K in three months.

Achieved 30% uplift in YARN resources and saved thousands of hours of core and memory waste.

Achieved more than 50% reduction of instance costs for a savings of over $1.1 million over 14 months.

Spark Application Waste Still Exists
Despite Traditional Optimizations

Infrastructure optimizations such as Managed Autoscaling, Spark Dynamic Allocation, and configuration tuning don’t eliminate the problem of application waste. Pepperdata can automatically save you 30% or more within your applications.

app level framework

Pepperdata Capacity Optimizer

  • (1) icon homepage pco instance hours

    Reduces instance hours and costs

    Save an average of 30-47 percent on Spark workload costs on Amazon EMR and Amazon EKS.

  • (1) icon homepage pco spark clusters

    Optimizes Spark clusters for efficiency

    Minimize (or eliminate) waste in Spark to run more applications without additional spend.

  • (1) icon homepage pco manual tuning

    Eliminates manual tuning and tweaking

    Free developers from the tedium of managing individual apps so they can focus on more innovative and strategic tasks.

Minimize Operational Costs, Maximize Savings

Data from 2023 Pepperdata TPC-DS Benchmark

41.8%

Cost Savings: Reduced instance hour consumption

45.5%

Improved Performance: Decreased application runtime

26.2%

Increased Throughput: Uplift in average concurrent container count

*TPC-DS is the Decision Support framework from the Transaction Processing Performance Council. TPC-DS is an industry-standard big data analytics benchmark. Pepperdata’s work is not an official audited benchmark as defined by TPC. TPC-DS benchmark results (Amazon EKS), 1 TB dataset, 500 nodes, and 10 parallel applications with 275 executors per application.

 

Customers Love Pepperdata

If you’re running Spark, give us 6 hours,
We’ll save you 30% on top of everything you’ve already done.

If you’re running Spark, give us 6 hours, We’ll save you 30% on top of everything you’ve already done.

If you’re running Spark, give us 6 hours, We’ll save you 30% on top of everything you’ve already done.

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Cloud Cost Management

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Cloud Management and Cloud Cost Management

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Enterprise Cloud Cost Management

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Benjamin S.
VP Technical Operations
Mid-Market Organization

“Improves spark report performance and saves overall compute spend”

What do you like about Pepperdata Capacity Optimizer?

“The ease of installation, great dashboards for cost and capacity visibility.

What problems is Pepperdata Capacity Optimizer solving?

“Lowering our overall cost.”

8/12/24
Review collected by and hosted on G2.com.

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Verified User
Banking
Enterprise

“Great Easy to use Product. A must for ETL and Big Data”

“Capacity Optimizer is a simple easy to implement – easy to use application that will save you money right from the get go.”

“Right out of the box you will see a 10 to 15 % savings. The support is top notch – they go above and beyond in getting the most out of the product. This is a no brainer for any Big Data workload.”

8/12/24
Review collected by and hosted on G2.com.

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Rahul C.,
Senior Director,
Enterprise Company

“Saved 75% cost on [Amazon] EMR”

“The capacity optimizer helped us to reduce the wastage on EMR clusters and increased the efficiency.”

“For one of the clusters – the savings was as big as 75%. For others we are seeing at least 30% savings.”

5/23/2024

Review collected by and hosted on G2.com.

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Lee G.
Mid-market organization

“Save money on your big data workloads”

“The capacity optimizer has been proven to save a lot of money. What I like best about the product, though, is the support we have received throughout our journey of migrating our EMR clusters from EC2 to EKS.”
—2/13/2024

gartner peer insights

Chief Data Architect, DPI

“The Missing Link In Large Scale YARN Cluster Management”

Getting up and running effectively took a little time, but now that we use of the product for ongoing monitoring and operations it’s hard to understand how we were getting by without it.

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“Pepperdata lets us see inside our ephemeral clusters even after they’ve been deleted.”

Being able to see the memory, cpu, io and other cluster metrics help us to appropriately size the clusters and tune our jobs.
Review collected by and hosted on G2.com.

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Sr. Software Engineer, Cloud Infrastructure

“Best for spark application monitor”

Easy to navigate for all metrics related to spark job, capture all yarn-related metrics. we can search by application id easily. multiple realm is also useful for EMR spark

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Consultant, 08/28/2022

“Pepperdata helps us in optimizing our day to day tasks.”

Its easy to go through the UI and get the stats of the tasks and see the errors and optimize them accordingly. Review collected by and hosted on G2.com.

Explore More

Looking for a safe, proven method to reduce waste and cost by up to 47% and maximize value for your cloud environment? Sign up now for a free cost optimization demo to learn how Pepperdata Capacity Optimizer can help you start saving immediately.